Instructions to use google/bert_uncased_L-4_H-256_A-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/bert_uncased_L-4_H-256_A-4 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/bert_uncased_L-4_H-256_A-4", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8baf2965303ee3eb136b0fce5ec3318f281f2b4111936db6781aaeaf94c7ed2c
- Size of remote file:
- 45.1 MB
- SHA256:
- 01671831dfec6818302153919efbfd6ee4ad91dd9fba7f3649bdd6cb7b0f16e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.